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details BlockwiseConvolutionOptions< N > Class Template Reference VIGRA

#include <vigra/multi_blockwise.hxx>

Inheritance diagram for BlockwiseConvolutionOptions< N >:
BlockwiseOptions ConvolutionOptions< N > ParallelOptions

Additional Inherited Members

- Public Types inherited from ParallelOptions
enum  { Auto = -1, Nice = -2, NoThreads = 0 }
 
- Public Member Functions inherited from BlockwiseOptions
BlockwiseOptions & blockShape (const Shape &blockShape)
 
template<class T , int N>
BlockwiseOptions & blockShape (const TinyVector< T, N > &blockShape)
 
BlockwiseOptions & blockShape (MultiArrayIndex blockShape)
 
Shape const & getBlockShape () const
 
template<int N>
TinyVector< MultiArrayIndex, N > getBlockShapeN () const
 
- Public Member Functions inherited from ParallelOptions
int getActualNumThreads () const
 Get desired number of threads. More...
 
int getNumThreads () const
 Get desired number of threads. More...
 
ParallelOptions & numThreads (const int n)
 Set the number of threads or one of the constants Auto, Nice and NoThreads. More...
 
- Public Member Functions inherited from ConvolutionOptions< N >
ConvolutionOptions< dim > & filterWindowSize (double ratio)
 
ConvolutionOptions< dim > & innerScale (...)
 
ConvolutionOptions< dim > & outerScale (...)
 
ConvolutionOptions< dim > & resolutionStdDev (...)
 
ConvolutionOptions< dim > & stdDev (...)
 
ConvolutionOptions< dim > & stepSize (...)
 
ConvolutionOptions< dim > & subarray (Shape const &from, Shape const &to)
 

Detailed Description

template<unsigned int N>
class vigra::BlockwiseConvolutionOptions< N >

Option class for blockwise convolution algorithms.

Simply derives from vigra::BlockwiseOptions and vigra::ConvolutionOptions to join their capabilities.


The documentation for this class was generated from the following file:

© Ullrich Köthe (ullrich.koethe@iwr.uni-heidelberg.de)
Heidelberg Collaboratory for Image Processing, University of Heidelberg, Germany

html generated using doxygen and Python
vigra 1.11.0 (Fri May 19 2017)